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Immunocytochemistry and Immunohistochemistry

Immunocytochemistry and Immunohistochemistry

Immunocytochemistry (ICC) and immunohistochemistry (IHC) are techniques that use antibodies to check for specific proteins or antigens in a sample. The technique was first published by Albert Coons in 1941 to detect the presence of pneumococcal antigen in tissue sections from mice infected with Pneumococcus. Immunocytochemistry helps localization of proteins or antigens in individual cells like blood cells, stem cells, etc., while immunohistochemistry does the same for tissue samples.
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Related Experiment Video

Updated: May 23, 2026

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma

Multiplexed Fluorescent Immunohistochemical Staining, Imaging, and Analysis in Histological Samples of Lymphoma

Published on: January 9, 2019

A pathologist-in-the-loop IHC antibody test selection using the entropy-based probabilistic method.

Dmitriy Shin¹, Gerald Arthur, Charles Caldwell

¹Department of Pathology and Anatomical Sciences, University of Missouri.

Journal of Pathology Informatics

|March 23, 2012

Summary

This summary is machine-generated.

This study introduces an informatics tool to optimize immunohistochemistry (IHC) antibody selection, reducing required tests threefold. The method streamlines IHC processes, cutting costs and improving diagnostic consistency for pathologists.

Keywords:

Antibody test selection clinical decision support computer--aided pathology diagnosis entropy maximization knowledge representation

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A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood

A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood

Published on: February 8, 2016

Area of Science:

Biomedical Informatics
Pathology
Molecular Diagnostics

Background:

Immunohistochemistry (IHC) is crucial for protein expression analysis in diseased tissues.
Pathologists face challenges remembering numerous antigen characteristics across diseases.
Increasing complexity in molecular pathology burdens pathologists, raising IHC costs and variability.

Purpose of the Study:

To develop an informatics tool for optimizing IHC antibody selection.
To assist pathologists in navigating complex IHC diagnostic processes.
To reduce the burden and improve the accuracy of IHC studies.

Main Methods:

Developed an antibody test optimized selection method.
Utilized extensions of Shannon's information entropies and Bayesian probabilities.
Dynamically built an efficient diagnostic tree for antibody selection.

Main Results:

The proposed method achieved a threefold reduction in necessary antibody tests.
Comparative analysis validated the method against expert and WHO guidelines.
Demonstrated significant efficiency in reaching diagnostic conclusions.

Conclusions:

The developed method streamlines IHC antibody test selection.
Significant cost reduction in IHC studies is achievable.
Reduced inter- and intra-pathologist variability in IHC decision-making.